Decisions that matter before
and after the first commit.
A deliberately small library for deciding what deserves a company, what must be true before building, and what can still kill it in production.
Evidence-native regulated operations: the company we would co-build
Corteus's working venture thesis. In regulated operations the costly step is proving an answer, not producing it. What a partner brings, and when we stop.
What a real eval suite looks like, and how to ask for it
A plain-English guide for investors and non-technical founders on what AI evals are, what a real suite contains, and how to tell evidence from theater.
AI startup red flags: the technical ones investors miss
Eight technical AI startup red flags non-technical investors can catch by ear in a pitch, with the follow-up question that confirms each one.
AI due diligence vs software due diligence
Why AI deals break standard software diligence: 4 gaps code scans miss, from eval quality to wrapper depth, before investors write a check this month.
How to evaluate an AI startup without a technical background
A no-code investor guide with 6 questions, good and bad answer patterns, and when to bring one engineer in before a term sheet or check for AI seed deals.
The Wrapper Test: will this AI product survive the next model release?
An 8-question Wrapper Test for investors: how to tell whether an AI product has data, workflow depth, evals, and customers a model release cannot copy.
AI agent platforms compared, before you commit
Compare AWS Bedrock AgentCore, OpenAI, Claude with MCP, LangGraph, and custom builds on lock-in, cost, and control before OpenAI's August 26, 2026 shutdown.
Build vs buy for AI products
A build vs buy framework for AI products: why 76% of enterprise AI is now bought, when building wins anyway, and the switching-cost math founders skip.
Fractional CTO vs dev agency vs technical co-founder
Fractional CTOs bill $150 to $500 an hour, US agencies charge $100 to $149, and a co-founder search can take a year. What each option really costs you.
How much does it cost to build an AI product in 2026
A verified 2026 cost breakdown for building an AI product: salaries, per-token API prices, data work, and why regulated systems cost 3 to 10 times more.
How to evaluate an AI startup's technology before investing
Five questions that reveal whether an AI startup's technology is real before you invest, and what honest answers sound like when $445 million is at stake.
Questions to ask an AI vendor about security
Seven security questions to ask any AI vendor before you sign, with the good answer and the dodge for each, from training data to SOC 2 and incident history.
When not to use AI agents
Gartner expects over 40% of agentic AI projects to be canceled by 2027. A practical four-question test for spotting tasks where an agent is the wrong tool.
How to safely run AI agents in your business
AI agents can boost productivity by 37%, but they need strict governance to protect sensitive data and systems. Learn how to control them.
Stripe's lesson: Why focused AI agents excel in compliance
Stripe handles $1.4 trillion in payments annually. Learn how they use AI agents to cut compliance review time by 26% while keeping humans in control.
Why your AI assistant might be sharing too much private data
New research reveals that 9 widely used AI agents often overshare private business data, even when completing tasks successfully, posing a significant risk.
How insurance brokerages are using AI to get work done faster
Insurance brokerages are saving about 10 hours per user per week with AI that understands their specific business needs, not just general chat.
How companies actually get value from AI
A plain guide to what a company has to figure out before AI pays off, built around three questions every business is asking about it right now.
CEO-Bench: can AI agents run a company for 500 days?
A Princeton test puts AI agents in charge of a fake software company for 500 days. Most went broke. Two finished rich. Here is what that tells you.
Why AI agents fail in production and how failure detection fixes it
When an AI agent gets something wrong, the mistake usually hides several steps back. A new AWS tool reads the agent's own logs and tells you which step broke and why.
How Rocket Close cut title work with an AI that takes actions
A real company put an AI agent on its slowest, most paperwork-heavy task and cut contact center calls and emails by 30 percent. Here is what it did, in plain terms.
How to tell if an AI agent is actually working
A right answer can hide a broken AI agent. A new AWS toolkit checks the steps, not just the final reply, and one test scored faithfulness at 32 percent.
No posts under this topic yet.